MGSR: 2D/3D Mutual-Boosted Gaussian Splatting for High-Fidelity Surface Reconstruction Under Various Light Conditions
Abstract
Novel view synthesis (NVS) and surface reconstruction (SR) are essential tasks in 3D Gaussian Splatting (3DGS). Despite recent progress, these tasks are often addressed independently, with GS-based rendering methods struggling under diverse light conditions and failing to produce accurate surfaces, while GS-based reconstruction methods frequently compromise rendering quality. This raises a central question: must rendering and reconstruction always involve a trade-off? To address this, we propose MGSR, a 2D/3D Mutual-boosted Gaussian Splatting for Surface Reconstruction that enhances both rendering quality and 3D reconstruction accuracy. MGSR introduces two branches--one based on 2DGS and the other on 3DGS. The 2DGS branch excels in surface reconstruction, providing precise geometry information to the 3DGS branch. Leveraging this geometry, the 3DGS branch employs a geometry-guided illumination decomposition module that captures reflected and transmitted components, enabling realistic rendering under varied light conditions. Using the transmitted component as supervision, the 2DGS branch also achieves high-fidelity surface reconstruction. Throughout the optimization process, the 2DGS and 3DGS branches undergo alternating optimization, providing mutual supervision. Prior to this, each branch completes an independent warm-up phase, with an early stopping strategy implemented to reduce computational costs. We evaluate MGSR on a diverse set of synthetic and real-world datasets, at both object and scene levels, demonstrating strong performance in rendering and surface reconstruction. Code is available at https://github.com/TsingyuanChou/MGSR.
Cite
Text
Zhou et al. "MGSR: 2D/3D Mutual-Boosted Gaussian Splatting for High-Fidelity Surface Reconstruction Under Various Light Conditions." International Conference on Computer Vision, 2025.Markdown
[Zhou et al. "MGSR: 2D/3D Mutual-Boosted Gaussian Splatting for High-Fidelity Surface Reconstruction Under Various Light Conditions." International Conference on Computer Vision, 2025.](https://mlanthology.org/iccv/2025/zhou2025iccv-mgsr/)BibTeX
@inproceedings{zhou2025iccv-mgsr,
title = {{MGSR: 2D/3D Mutual-Boosted Gaussian Splatting for High-Fidelity Surface Reconstruction Under Various Light Conditions}},
author = {Zhou, Qingyuan and Gong, Yuehu and Yang, Weidong and Li, Jiaze and Luo, Yeqi and Xu, Baixin and Li, Shuhao and Fei, Ben and He, Ying},
booktitle = {International Conference on Computer Vision},
year = {2025},
pages = {27295-27304},
url = {https://mlanthology.org/iccv/2025/zhou2025iccv-mgsr/}
}